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A general equilibrium evaluation of the fiscal costs of trade liberalization in Ukraine

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Abstract

The establishment of an Association Agreement/Deep and Comprehensive Free Trade Agreement (AA/DCFTA) with the European Union (EU) would be the next significant step towards Ukraine’s deeper integration into the world economy. Despite widely expected additional welfare gains, the signing of the AA/DCFTA at the Third Eastern Partnership summit in November 2013 in Vilnius was suspended by the Ukrainian government due to geopolitical concerns and a severe economic and financial crisis in Ukraine coming along with high external debt and a substantial public budget deficit. This puts the fiscal consequences of Ukraine’s continued liberalization into focus, as transition and developing countries face higher fiscal costs associated with trade integration. Accordingly, this paper contributes to the literature by analyzing the part of the potential EU-Ukraine DCFTA which leads to a loss of tariff revenues, namely the tariff elimination. In particular, we apply a static Computable General Equilibrium (CGE) model for the single small open economy of Ukraine and focus on the effects of Ukraine’s unilateral tariff elimination by simulating three scenarios reflecting different means to compensate for the loss of tariff revenues. It turns out to be important to take these costs into consideration while modeling trade liberalization, as the results vary significantly across the scenarios.

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Notes

  1. If the EU would not be considered as a single trading partner, Russia would be on top.

  2. As one of the former republics of the Soviet Union, Ukraine is ranked among the countries with transition economies (http://www.worldbank.org/depweb/english/beyond/global/glossary.html). At the same time it is classified as a developing country according to the World Bank classification, which is based on gross national income per capita (http://data.worldbank.org/about/faq/specific-data-series).

  3. This means that Non-Tariff Barriers (NTBs) and the liberalization of service trade are also not taken into account.

  4. See Bouët (2008), p. 22.

  5. The effects in the EU are anyway expected to be rather small as the Ukrainian import share accounted only for 0.7 % of the total EU imports in 2009.

  6. See Bouët (2008), p. 56.

  7. See Emerson et al. (2006) and Ecorys and CASE-Ukraine (2007).

  8. The general and mostly applied method to deal with reduced tariff revenues in a CGE model is to increase lump sum taxes. This is an unrealistic assumption because lump sum taxes are an artificial construct (see von Cramon-Taubadel et al. 2010).

  9. The shares are calculated using the treasury reports of the Accounting Chamber of Ukraine, available in Ukrainian at http://www.ac-rada.gov.ua/.

  10. Concerning the importance of the revenue replacement assumption see for example Abbott et al. (2009).

  11. See Rutherford (1999) and Boehringer et al. (2003).

  12. See Eq. (4).

  13. This assumption is based on Armington (1969). The preferences of consumers considering the substitutability between domestic goods and imports are modeled using so-called Armington elasticities (esdm), which are exogenous parameters in the model. See also Dervis et al. (1982), pp. 221–223, 226–227.

  14. \(\overline{L}\) and \(\overline{K}\) are defined as fixed labor and capital endowments, w s and r represent the real factor returns (real wages and interest rate).

  15. C j is the consumption of good j and τ j represents the consumption tax rate for good j.

  16. The poverty line is calculated following the methodology of the Ministry of Economy of Ukraine, available in Ukrainian at http://zakon.rada.gov.ua/cgi-bin/laws/main.cgi?nreg=z0401-02.

  17. Including capital income in state-owned sectors with sector-specific capital (r sp K sp ): mining and pipeline transportation (a04 and a24P).

  18. Consumption levels of public services are determined by a Cobb-Douglas function.

  19. We do not consider the current account balance in the model as there are no imbalances. We hold a balanced current account to be able to isolate the effects of trade liberalization.

  20. See Rutherford and Paltsev (1999) and Rutherford (1999).

  21. See King (1985).

  22. Concerning the sectoral structure two changes were made in the SAM compared to the original I–O Table. The heat supply sector was added to the electric energy sector (a17) and the pipeline transit of oil and gas (a24P) was separated from the transportation sector.

  23. The State Statistics Committee of Ukraine.

  24. Exports and imports for the ROW region are obtained as a residual.

  25. Following WTO et al. (2007), pp. 187–188.

  26. The FTA was established in 1999.

  27. In the benchmark scenario tariff revenues amount to 4.03 % of the public budget.

  28. Note that Ukraine is not included in those analyses. However, it also belongs to a group of middle income countries.

  29. This trend cannot be observed for Ukraine’s previous trade liberalization as in case of the WTO accession public spending steadily increased from 241,490 millions UAH in 2008 to 333,459 millions UAH in 2011 according to the Accounting Chamber of Ukraine. Nonetheless, it is one option for future reforms.

  30. We allow only for an endogenous increase of indirect tax on final, public and intermediate demand as well as on investments. This refers to the issue of optimal taxation as illustrated by Auriol and Warlters (2012).

  31. According to the laws of Ukraine: \(\mathcal{N}^{\underline{\circ}}\) 797-VI from 25.12.2008 “About amendments to some laws of Ukraine on taxation”, \(\mathcal{N}^{\underline{\circ}}\) 1202-VI from 31.03.2009 “About amendments to some laws of Ukraine on excise duty”. For instance, the excise duty on ethyl alcohol was increased from 21.5 UAH to 34 UAH per liter and the tax rate on tobaccos was raised from 8 to 16 %.

  32. See article 2.2.2 of the treasury report of the Accounting Chamber of Ukraine for 2009, available in Ukrainian at http://www.ac-rada.gov.ua/control/main/uk/publish/article/16728123.

  33. See European Parliament (2011), article 1(e).

  34. See European Commission (2013), available athttp://europa.eu/rapid/press-release_MEMO-13-1146_en.htm.

  35. Terms of trade effects are excluded by the assumption of a one-country, small open economy model.

  36. This foreign aid accounts for about 0.4 % of Ukrainian GDP or 1.63 % of the public budget in 2007.

  37. GDP effects were expected to be rather small as economic growth is not modeled endogenously and therefore trade can affect GDP only via the mechanism of resource allocation (Abbott et al. 2009).

  38. These sectors account for 82.8 % of government spending (see Table 10).

  39. See Fig. 6 or Table 11.

  40. Table 9 indicates labor intensity for the three aforementioned sectors and Table 8 shows that the skilled labor demand is much higher in these industries compared to the unskilled labor type. Therefore, we conclude that public services are characterized by skilled labor-intensive production.

  41. Following the Heckscher-Ohlin and Stolper-Samuelson theorems, see Feenstra (2004), pp. 15, 32, 174.

  42. For a formal discussion of the equivalent variation measure see for example Weber (2010).

  43. See Table 1.

  44. The welfare increase for poor households is smaller than in S1. This is explained by the relatively lower increase in the wage rate for unskilled labor, which is the only production factor owned by poor households.

  45. See Kemp and Wan (1976), Feenstra (2004), pp. 192–196 and WTO (2011), pp. 100–102.

  46. See Table 13.

  47. Except for production of hydrocarbons in S2 where we observe a slight decrease of imports because of price changes in this sector: the relative import price of hydrocarbons remains almost unchanged while the relative domestic supply price decreases.

  48. Construction gains from the elimination of import tariffs for non-metallic mineral products (initial value 7.07 %) which allows for higher output and exports.

  49. Our data do not consider land as a separate production factor. This means that capital includes also land as an input for production.

  50. The strongest fall of factor and intermediate demand is observed in food-processing and production of non-metallic mineral products, agriculture, fishery and petroleum refinement.

  51. These sectors use much more labor and capital than intermediate inputs for production (see Table 8), so that domestic supply prices increase with higher factor remuneration.

  52. These include the activities from agriculture up to electric energy and heat supply.

  53. The only qualitative difference occurs in S2 for rural poor households which increase their consumption by 0.01 % in comparison with the reduction by 0.01 % before. The reason is the benefit of these households from the higher increase (+0.22 %) of the wage rate for unskilled labor (the sole production factor they are endowed with) in 2004.

  54. See Jensen et al. (2005), p. 25.

  55. A comparable sensitivity analysis can be found in Jensen and Tarr (2011).

  56. This value is chosen because Armington elasticities of zero are not theoretically possible.

  57. We have also tested the elasticity of transformation between export destinations (etreg) but there is no influence on the welfare changes and other macroeconomic results.

  58. All reported results except for deviations and trade flows are represented as raw simulation results and show changes relative to the benchmark values of 1.

  59. The 95 % confidence interval is calculated for each scenario separately on the basis of robustness checks.

  60. Other criticism refers to the not considered peculiarities of the Ukrainian economy such as unemployment, rigidities on factor markets and economies of scale (e.g. in metallurgy, manufacture of machinery and equipment). These extensions are a matter of further research.

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Acknowledgments

The authors thank the editor, three anonymous referees, Volker Clausen, Richard Frensch, Jürgen Jerger, Veronika Movchan, Ferdinand Pavel, Hannah Schürenberg-Frosch, and participants at EcoMod2012 (Seville), 15th Annual Conference on Global Economic Analysis “New Challenges for Global Trade and Sustainable Development” (Geneva), 5th FIW Research Conference “International Economics” (Vienna), 13th Annual Conference of the International Network for Economic Research (London), Thirteenth Annual Conference of the European Trade Study Group (Copenhagen), International Workshop on Recent Issues in European Economic Integration and EU Enlargement (Brussels), XIIth International Academic Conference on Economic and Social Development (Moscow), 13. Göttinger Workshop “Internationale Wirtschaftsbeziehungen” (Göttingen), 25th Research Seminar of the Managing Economic Transition network (Brighton) for valuable comments and helpful suggestions.

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Authors and Affiliations

  1. Institute for East and Southeast European Studies, University of Regensburg, Landshuter Str. 4, 93047, Regensburg, Germany

    Miriam Frey

  2. Chair for International Economics, University of Duisburg-Essen, Universitaetsstr. 12, 45117, Essen, Germany

    Zoryana Olekseyuk

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  1. Miriam Frey
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Correspondence to Miriam Frey.

Appendix

Appendix

See the Tables 7, 8, 9, 10, 11, 12 and 13.

Table 7 Countries’ aggregation into trading regions
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Table 8 Initial input and output structure of production sectors
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Table 9 Factor intensity of production sectors
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Table 10 Consumption shares (in %)
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Table 11 Disaggregate results
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Table 12 Sector-specific results
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Table 13 Public spending (UAH bn)
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Frey, M., Olekseyuk, Z. A general equilibrium evaluation of the fiscal costs of trade liberalization in Ukraine. Empirica 41, 505–540 (2014). https://doi.org/10.1007/s10663-014-9249-z

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